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Overcoming Noisy and Irrelevant Data in Federated Learning

Overcoming Noisy and Irrelevant Data in Federated Learning

Tiffany Tuor
Shiqiang Wang
Bongjun Ko
Changchang Liu
K. Leung
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Papers citing "Overcoming Noisy and Irrelevant Data in Federated Learning"

4 / 4 papers shown
Title
How does Disagreement Help Generalization against Label Corruption?
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu
Bo Han
Jiangchao Yao
Gang Niu
Ivor W. Tsang
Masashi Sugiyama
NoLa
45
778
0
14 Jan 2019
LEAF: A Benchmark for Federated Settings
LEAF: A Benchmark for Federated Settings
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
FedML
118
1,410
0
03 Dec 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
217
1,698
0
14 Apr 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
201
8,807
0
25 Aug 2017

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